scholarly journals Temporal and spatial variability of extreme snowfall indices over northern Xinjiang from 1959/1960 to 2008/2009

2013 ◽  
Vol 1 (6) ◽  
pp. 7059-7092 ◽  
Author(s):  
S. P. Wang ◽  
F. Q. Jiang ◽  
R. J. Hu ◽  
Y. W. Zhang
Keyword(s):  
Temporal Trends ◽  
Kendall Test ◽  
Winter Precipitation ◽  
Kriging Interpolation ◽  
Significance Level ◽  
Northern Xinjiang ◽  
The North ◽  
Mk Test ◽  
Increasing Trends

Abstract. Plentiful snowfall is an important resource in northern Xinjiang. However, extreme snowfall events can lead to destructive avalanches, traffic interruptions or even the collapse of buildings. The daily winter precipitation data from 18 stations in northern Xinjiang during 1959/1960–2008/2009 were selected for purpose of analyzing long-term variability of extreme snowfall events. Five extreme snowfall indices, Maximum 1 day snowfall amount (SX1day), Maximum 1-weather process snowfall amount (SX1process), Blizzard days (DSb), Consecutive snow days (DSc) and Blizzard weather processes (PSb), were defined and utilized to quantitatively describe the intensity and frequency of extreme snowfall events. Temporal trends of the five indices were analyzed by Mann–Kendall test and simple linear regression, and their trends were interpolated using universal kriging interpolation. Temporally, we found that most stations have upward trends in the five indices of extreme snowfall events, and over entire northern Xinjiang, they were all increasing at the 0.01 significance level (MK test), with the linear tendency rates of 0.49 mm (10 a)−1 (SX1day), 0.89 mm (10 a)−1 (SX1process), 0.024 days (10 a)−1 (DSb), 0.14 days (10 a)−1 (DSc), and 0.069 times (10 a)−1 (PSb) respectively. Meanwhile, obvious decadal fluctuations besides long-term increasing trends are identified. Trends in the intensity and frequency of extreme snowfall events show a~distinct difference spatially. In general, trends of five indices were found shifting from decreasing to increasing from the northeast to the southwest and from the north to the south of northern Xinjiang. Furthermore, the regions covered by increasing or decreasing extreme snowfall events were identified, implying the hot or cold spots for extreme snowfall events changes. These results may be helpful for northern Xinjiang on the regional and local resource and emergency planning.

scholarly journals Trend Analysis of Long-Term Reference Evapotranspiration and Its Components over the Korean Peninsula

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1373 ◽  
Author(s):  
Mona Ghafouri-Azar ◽  
Deg-Hyo Bae ◽  
Shin-Uk Kang
Keyword(s):  
Solar Radiation ◽  
Korean Peninsula ◽  
Reference Evapotranspiration ◽  
Temporal Trends ◽  
Weather Data ◽  
Energy Term ◽  
The North ◽  
Dominant Component ◽  
Mk Test ◽  
Increasing Trends

In this study, the spatial and temporal trends of reference evapotranspiration (ETo) and its components consisting of the energy term (ENo) and the aerodynamic term (AEo) were considered over the Korean Peninsula. The T-test and Mann–Kendall (MK) test were used to detect parameter trends after removing the effect of serial correlation from annual and seasonal time series between 1980 and 2017. Due to the lack of solar-radiation data for North Korea (NK), a regionally calibrated model based on South Korea (SK) weather data was developed to estimate daily solar radiation in NK. The results showed that spatial distribution of the ETo increased southward in the range from 705 mm/year in the northeast to 1195 mm/year in the southeast of the Korean Peninsula. The spatial patterns of the ENo and AEo varied from the minimum in the north and increased southward, reaching their maximum values in the southern parts of the Korean Peninsula. The mean annual ETo values of SK and NK were also compared. Over the 37-year period, mean annual evapotranspiration in SK was approximately 18% higher than that in NK. Moreover, mean areal ENo and AEo in SK were higher than in NK. The trend of the ENo on annual and seasonal scales was also upward. In contrast, the trend of the AEo decreased over the Korean Peninsula through all seasons and annual scales. These opposite trends in the ENo and AEo parameters mitigated the significant trends of the ETo. Finally, the stronger significant upward trend of the energy term led to significant increasing trends of ETo on the Korean Peninsula, with ENo being the dominant component in the increase of the ETo.

scholarly journals Trends in urban storm water quality in Tallinn and influences from stormflow and baseflow

2016 ◽  
Vol 2 (1) ◽  
Author(s):  
Bharat Maharjan ◽  
Karin Pachel ◽  
Enn Loigu
Keyword(s):  
Temporal Trends ◽  
Oxygen Demand ◽  
Road Dust ◽  
Kendall Test ◽  
P Value ◽  
Upward Trend ◽  
Monotonic Trend ◽  
Acidic Rain ◽  
Interpretation Of Change

Temporal trends provide a good interpretation of change in stormwater quality over time. This study aimed to analyse trends and influences due to stormflow and baseflow. Grab samples of 18-19 years from 1995 to 2014 recorded at outlets of 7 Tallinn watersheds were analysed for monotonic trend through seasonal Mann Kendall test for long-term, short-term, baseflow and stormflow. Statistically significant downward trends (P-value (p) < 0.05) were found for 6 – hydrocarbon (HC), 1 – suspended solids (SS), 3 – biological oxygen demand (BOD), 4 – total nitrogen (TN) and 2 – total phosphorus (TP) out of 7 sampling outlets over the last 10 years. Less significant decreasing trends (p > 0.05 and < 0.2) for 3 – SS, 1 – BOD, 1 – TN and 1 – TP were identified. Statistically significant long-term upward trends of pH were re-vealed in 5 basins, which reduced to 2 with 5 less significant upward trends over the 10 year period, indicating improve-ments in pH reduction. Härjapea has the highest pH without trend but it includes an upward trend of TN at p = 0.051. The highly possible causes for downward trends are street sweeping, sewer network improvement, decline in sub-urban agri-cultural areas, etc. The upward trend results of pH are related to increased alkalinisation due to acidic rain, weathering of carbonate rocks, sewage discharge and alkaline road dust. In most of the basins, stormflow has more influence on trends than baseflow.

scholarly journals Temporal and spatial distributions of precipitation on the Huang-Huai-Hai Plain during 1960–2019, China

2021 ◽  
Author(s):  
Minhua Ling ◽  
Hongbao Han ◽  
Xingling Wei ◽  
Cuimei Lv
Keyword(s):  
Spatial Distribution ◽  
Large Scale ◽  
Kendall Test ◽  
Winter Precipitation ◽  
Annual Precipitation ◽  
Temporal And Spatial Distribution ◽  
Global Pattern ◽  
The North ◽  
Variance Contribution ◽  
Temporal And Spatial

Abstract The Huang-Huai-Hai Plain is an important commercial grain production base in China. Understanding the temporal and spatial variations in precipitation can help prevent drought and flood disasters and ensure food security. Based on the precipitation data for the Huang-Huai-Hai Plain from 1960 to 2019, this study analysed the spatiotemporal distribution of total precipitation at different time scales using the Mann–Kendall test, the wavelet analysis, the empirical orthogonal function (EOF), and the centre-of-gravity model. The results were as follows: (1) The winter precipitation showed a significant upward trend on the Huang-Huai-Hai Plain, while other seasonal trends were not significant. (2) The precipitation on the Huang-Huai-Hai Plain shows a zonal decreasing distribution from southeast to northwest. (3) The application of the EOF method revealed the temporal and spatial distribution characteristics of the precipitation field. The cumulative variance contribution rate of the first two eigenvectors reached 51.5%, revealing two typical distribution fields, namely a ‘global pattern’ and a ‘north-south pattern’. The ‘global pattern’ is the decisive mode, indicating that precipitation on the Huang-Huai-Hai Plain is affected by large-scale weather systems. (4) The annual precipitation barycentres on the Huang-Huai-Hai Plain were located in Jining city and Taian city, Shandong Province, and the spatial distribution pattern was north-south. The annual precipitation barycentres tended to move southwest, but the trend was not obvious. The annual precipitation barycentre is expected to continue to shift to the north in 2020.

scholarly journals Multi-annual analysis and trends of the temperatures and precipitations in West Anatolia

2017 ◽  
Vol 8 (3) ◽  
pp. 456-473 ◽  
Author(s):  
Turgay Partal
Keyword(s):  
Kendall Test ◽  
Temperature Data ◽  
Significance Level ◽  
Time Frequency ◽  
Pettitt Test ◽  
Frequency Representation ◽  
Mann Kendall Test ◽  
Scale Levels ◽  
Increasing Trends ◽  
Periodic Components

This study has been carried out to analyze the historical precipitation and temperature data for West Anatolia (Turkey) to understand the annual and multi-annual changes. The wavelet transform technique was used for time–frequency representation of the data. The trends in the data were estimated with the non-parametric Mann–Kendall test. A change point in the time series was determined by the Pettitt test. According to the wavelet analysis, some strong short-term periodical events at the scale levels of 1–4 were determined. The application of the Mann–Kendall test resulted with the identification of some decreasing trends in the observed annual precipitations and also in some periodic components, such as in 32 yearly periodic components. As well, 16 yearly periodic components of the temperature data showed very strong increasing trends at the 5% significance level.

scholarly journals Analysis of rainfall trends over Tripura

MAUSAM ◽  
2022 ◽  
Vol 73 (1) ◽  
pp. 27-36
Author(s):  
RANJAN PHUKAN ◽  
D. SAHA
Keyword(s):  
Heavy Rainfall ◽  
Monsoon Season ◽  
Rainfall Variability ◽  
Kendall Test ◽  
Annual Rainfall ◽  
The North ◽  
Rainfall Trends ◽  
Annual Scale ◽  
Increasing Trends ◽  
Rainy Days

Rainfall in India has very high temporal and spatial variability. The rainfall variability affects the livelihood and food habits of people from different regions. In this study, the rainfall trends in two stations in the north-eastern state of Tripura, namely Agartala and Kailashahar have been studied for the period 1955-2017. The state experiences an annual mean of more than 2000 mm of rainfall, out of which, about 60% occurs during the monsoon season and about 30% in pre-monsoon. An attempt has been made to analyze the trends in seasonal and annual rainfall, rainy days and heavy rainfall in the two stations, during the same period.Non-parametric Mann-Kendall test has been used to find out the significance of these trends. Both increasing and decreasing trends are observed over the two stations. Increasing trends in rainfall, rainy days and heavy rainfall are found at Agartala during pre-monsoon season and decreasing trends in all other seasons and at annual scale. At Kailashahar, rainfall amount (rainy days & heavy rainfall) is found to be increasing during pre-monsoon and monsoon seasons (pre-monsoon season). At annual scale also, rainfall and rainy days show increasing trends at Kailashahar. The parameters are showing decreasing trends during all other seasons at the station. Rainy days over Agartala show a significantly decreasing trend in monsoon, whereas no other trend is found to be significant over both the stations.  

scholarly journals Historical and Temporal Trends of Climatic Parameters in North East India

2017 ◽  
Vol 19 (4) ◽  
pp. 547-561 ◽  
Keyword(s):  
Meteorological Data ◽  
Temporal Trends ◽  
Maximum Temperature ◽  
Local Climate ◽  
Water Resources Systems ◽  
North East India ◽  
North East ◽  
Mk Test ◽  
Ne India ◽  
Increasing Trends

Accessing temporal trend of different meteorological parameters is essential for understanding the local climate changing pattern of a region. Quantitative estimates of the effect of climate change helps in understanding, planning, and management of water resources systems. In this study, monthly meteorological data were collected from 30 stations of north-east (NE) India for 1971–2010 and non-parametric Mann-Kendall (MK) test and Sen slope were employed for detection and quantification of significant temporal trends, respectively. An ESRI ArcGIS toolbar “ArcTrends” was used for the above mentioned tasks. The results obtained for rainfall were of mixed nature and both increasing and decreasing significant trends were found for different stations in different months. Most of the negative trends were found in the months of July–August (monsoon), whereas, more stations showed positive trends in April–May (pre-monsoon), and October–November (post-monsoon), indicating inter-seasonal shifting of rainfall without much change in the annual total. Number of rainy days was found to have positive trends in March–May (pre-monsoon) and negative trends in September–December. Except some positive trends during June–December in Manipur and Meghalaya, there were no significant trends in maximum temperature. In some stations, minimum temperature was found to have significant increasing trends throughout the year indicating a general rising trend in NE India. Some major towns like Guwahati, Imphal, Agartala and Kailashshahar showed significant positive trends in mean temperature, mostly during June–December. Mean relative humidity was, in general, found to be significantly increasing, especially during February–March. In some stations, wind speed was found to have significant negative trends throughout the year, with Agartala being the most affected.

scholarly journals Variability and trends of precipitation on lowand high-altitude stations in Serbia

2021 ◽  
pp. 14-23
Author(s):  
Igor Leščešen ◽  
Dragan Milošević ◽  
Rastislav Stojsavljević
Keyword(s):  
Linear Regression ◽  
High Altitude ◽  
Trend Analysis ◽  
P Value ◽  
Monthly Precipitation ◽  
Precipitation Data ◽  
Significance Level ◽  
Mk Test ◽  
Increasing Trends

For the trend analysis of the annual, seasonal and monthly precipitation linear regression and Mann-Kendall (MK) tests at the 5% significance level were applied. In this study, precipitation data from two stations in Serbia for the 1949-2019 period were used. Results indicate that increasing trends of precipitation for the selected station can be observed but these trends were not statistically significant according to MK test. Then again, MK test has shown that only on Palić station during autumn precipitations have statistically significant increase during the observed period with a p value of 0.0441 at the significant level p=0.005.

scholarly journals Long-term trends of climate change and its impact on crop growing season on Montreal Island

2016 ◽  
Vol 8 (1) ◽  
pp. 78-88
Author(s):  
Erika Bouchard ◽  
Zhiming Qi
Keyword(s):  
Climate Change ◽  
Daily Rainfall ◽  
Growing Season ◽  
Annual Rainfall ◽  
Climate Trends ◽  
Growing Season Length ◽  
Mk Test ◽  
Long Term Trends ◽  
Increasing Trends

Long-term trends in air temperature and precipitation under climate change were analyzed for two meteorological stations on the Island of Montreal: McGill (1872–1986) and Pierre-Elliott-Trudeau (P-E-T, formerly Dorval) Airport (1942–2014). A linear trendline analysis, the Mann–Kendall (MK) test and the two-sample Kolmogorov–Smirnov (KS) test were conducted to assess specific climate trends. On a 100-year basis, temperature increased 1.88°C (34%) and 1.18°C (19%) at the McGill and P-E-T Airport sites, respectively, while annual rainfall increased 23.9 mm y−1 (2.3%) and 138.8 mm y−1 (15%) over the same period. The frequency of 50% (every other year) and 95% (every year) annual maximum daily rainfall events showed decreasing trends for the McGill station, but increasing trends for the P-E-T Airport station. Growing degree-days and growing season length are prone to being influenced by climate change and are critical to managing agricultural activities in the Montreal region; both showed increasing trends. At the same time, the onset of the growing season occurred earlier as time progressed.

scholarly journals Disentangling the scarcity of near-natural Iberian hydrological resources since 1980s: a multivariate-driven approach

2021 ◽  
Author(s):  
Amar Halifa-Marín ◽  
Miguel Ángel Torres-Vázquez ◽  
Enrique Pravia-Sarabia ◽  
Marc Lemus-Cánovas ◽  
Juan Pedro Montávez ◽  
...  
Keyword(s):  
Water Cycle ◽  
Climate Change Impacts ◽  
Winter Precipitation ◽  
The Novel ◽  
Abrupt Decrease ◽  
The North ◽  
Run Off ◽  
Recent Debate ◽  
The North Atlantic Oscillation

Abstract. A significant abrupt decrease of Winter Precipitation (WP) has been noticed in the Iberian Peninsula since the 1980s related to atmospheric drivers. This contribution assesses the long-term variability of water resources based on a multivariate-driven approach. For this purpose, the novel dataset of Near Natural Water Inflows to Reservoirs of Spain (NENWIRES) was created. Results confirm that Winter Water Inflows (WWI) have been modulated by the sudden decline in WP. These drastic reductions of WP/WWI were mainly controlled by the enhancement of the positive phase of the North Atlantic Oscillation (NAOi+). Nonetheless, our results also highlight the anthropogenic/physical causes contributing to the 1980s shift in the hydroclimate series. The rise of temperature, the cropland abandonment and forest extension provoked evapotranspiration gains and run-off weakening. NENWIRES most humid catchments registered the decrease of WWI promoted by NAOi+ persistence/frequency, while the land greening-up and ET rises explain the WWI losses in the Iberian semiarid environments. This contribution sheds some light on the recent debate about magnitude/drivers of streamflow declining over southern Europe. Therefore, it might help water planning with the goal of mitigating the climate change impacts affecting the water cycle.

scholarly journals Elevation-dependent trends in extreme snowfall in the French Alps from 1959 to 2019

2021 ◽  
Author(s):  
Erwan Le Roux ◽  
Guillaume Evin ◽  
Nicolas Eckert ◽  
Juliette Blanchet ◽  
Samuel Morin
Keyword(s):  
Temporal Trends ◽  
Information Criterion ◽  
Warming Trend ◽  
High Elevation ◽  
Extreme Value ◽  
Mountain Range ◽  
French Alps ◽  
The North ◽  
Return Levels ◽  
Increasing Trends

Abstract. Climate change projections indicate that extreme snowfall are expected to increase in cold areas, i.e. at high latitude and/or high elevation, and to decrease in warmer areas, i.e. at mid-latitude and low elevation. However, the magnitude of these contrasted patterns of change and their precise relations to elevation at the scale of a given mountain range remain ill-known. This study analyzes annual maxima of daily snowfall based on the SAFRAN reanalysis spanning the time period 1959–2019, and provided within 23 massifs in the French Alps every 300 m of elevation. We estimate temporal trends in 100-year return levels with non-stationary extreme value models that depend both on elevation and time. Specifically, for each massif and four elevation ranges (below 1000 m, 1000–2000 m, 2000–3000 m and above 3000 m), temporal trends are estimated with the best extreme value models selected on the basis of the Akaike information criterion. Our results show that a majority of trends are decreasing below 2000 m and increasing above 2000 m. Quantitatively, we find an increase of 100-year return levels between 1959 and 2019 equal to +23 % (+32 kg m−2) on average at 3500 m, and a decrease of −10 % (−7 kg m−2) on average at 500 m. However, for the four elevation ranges, we find both decreasing and increasing trends depending on location. In particular, we observe a spatially contrasted pattern, exemplified at 2500 m: 100-year return levels have decreased in the north of the French Alps while they have increased in the south which may result from interactions between the overall warming trend and circulation patterns. This study has implications for natural hazards management in mountain regions.

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